83 citations · 125 across the 5 of their papers we have counts for
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cs.LG2019★ 83 cited
Active Federated Learning
Jack Goetz, Kshitiz Malik, Duc Bui +3
Federated Learning allows for population level models to be trained without centralizing client data by transmitting the global model to clients, calculating gradients locally, the…
cs.LG2019★ 37 cited
Federated User Representation Learning
Duc Bui, Kshitiz Malik, Jack Goetz +4
Collaborative personalization, such as through learned user representations (embeddings), can improve the prediction accuracy of neural-network-based models significantly. We propo…
cs.LG2018
Explore-Exploit: A Framework for Interactive and Online Learning
Honglei Liu, Anuj Kumar, Wenhai Yang +1
Interactive user interfaces need to continuously evolve based on the interactions that a user has (or does not have) with the system. This may require constant exploration of vario…